104 Marine Invertebrate Paleontology I

Wednesday, 7 November 2001
8:00 AM - 12:00 PM

PARTITIONING PHENOTYPIC VARIATION INTO GENOTYPE, ENVIRONMENT AND GXE INTERACTION AND WITHIN-COLONY FACTORS: IMPLICATIONS FOR MORPHOMETRIC ANALYSES (BRYOZOA)

Paper number: 104-5
Program: Technical Sessions
Time: 8:00 AM – 12:00 PM

Authors

Abstract

Using clonal replicates of Electra pilosa (L.) colonies grown in controlled environmental conditions, it is possible to partition sources of morphological variation of skeletal hardparts into their Genotype (G), Environment (E) and interaction (GxE) components. Preliminary studies demonstrated that these factors accounted for only about 40% of variation among measured zooecial characteristics, resulting in a Residual (variation unaccounted for in the model) of 60%. In addition to the factors Genotype and Tank (=Environment), within-colony sources of variation were evaluated with a nested ANOVA design for five zooecial characteristics (opesia and zooecia width and length and spine number): Patches of zooecia were nested within replicate colonies, and Columns and Rows of zooecia nested within Patches.

The large Residual reported in previous studies was reduced by two-thirds (to < 20%) when sources of within colony variation were accounted for in ANOVA Models. Significant environmental variation can be detected (Tank effect ~ 2–3%), even in experiments designed to minimize this source. Patch effect within colonies (~ 25–35%) was highly significant, and often was greater than that attributable to Genotype.

If the Patch effect is not treated as a separate factor in ANOVA, the resulting variance will either be misallocated to other factors (i.e. Genotype or Environment) if only a single patch is sampled per colony, or will be allocated to the Residual if zooids are pooled (sampled widely across the colony). Therefore, morphometric data should not be sampled from a single small fossil bryozoan fragment. Row and Column effects within patches were small, ~ 5–10%, but nonetheless significant. If Row and Column are omitted as factors in ANOVA, their variance does not affect the outcome for other factors and is accordingly allocated to the Residual.